Income and Wealth Inequality in the U.S.

by Ben Lorica (last updated Mar/2012)

Raising taxes for the richest households is an issue that surfaces each election cycle. Democrats who suggest an increase to the marginal tax rates for richest earners, are automatically accused of engaging in "class warfare". Below are graphs inspired by a recent post on Econbrowser. The share of income of the top earners has been on a steady upward trend since 1980, with the income (including capital gains) of the Top 10% earners hitting 50% in 2007 -- which of course meant the "bottom" 90% had to share the other 50% of all income! It certainly doesn't appear that a return to Clinton era marginal tax rates is unreasonable1.

I include income share excluding capital gains to emphasize that inequality persists even after you remove wealth gains from past bull markets.

"Top income share series are constructed using tax statistics. The use of tax data is often regarded by economists with considerable disbelief. .. shortcomings limit what can be said from tax data but this does not mean that the data are worthless. Like all economic data, they measure with error the "true" variable in which we are interested. As with all data, there are potential sources of bias but, as in other cases, we can say something about the possible direction and magnitude of the bias. Moreover, we can compensate for some of the shortcomings of the income tax data. It is true that income tax data cover only the taxpaying population, which, in the early years of income tax, was typically only a small fraction of the total population. As a result, tax data cannot be used to describe the whole distribution but we can estimate the upper part of the Lorenz curve, i.e., top income shares."

Among several countries for which the researchers were able to obtain data, the US had the most income concentrated in the Top 1% (17.42% in 2005). Their database also lets us look at long-term trend: in 1949 the share of Top 1% earners in the US, was comparable with other countries in the study.

To further help you evaluate income concentration in the US relative to other countries, I constructed simple scatterplots using two metrics: (1) Income Share of Top 1% Earners (horizontal axis), and (2) Income Share of Top 0.1% Earners (vertical axis). Note that for the graph below, both (1) & (2) exclude realized capital gains. To isolate "outliers", I highlighted the mean value of each axis (the "dashed" lines) as well as the regions within one standard deviation of the mean of each axis. (To help isolate the US in the scatterplot, I used a different color & dot size for the US.)

For the period around 2005, the US scored as follows

(1) Income Share of Top 1% Earners (horizontal axis) => 17.42%

(2) Income Share of Top 0.1% Earners (vertical axis) => 7.7%

At least for the period around 2005, the share of the top earners in the US, was much higher than other countries3 studied closely by Saez and his colleagues. If you switch the graph to the period around 1949, the US was comparable to other countries.

Income Mobility

The previous graphs indicate that the share of the top earners in the US have grown, particularly over recent decades. Critics of inequality studies point out that mobility - the movement of individuals & families up and down the economic ladder - make annual income a poor measure of economic well-being. But another set of studies have shown that income mobility has remained stable - even as the share of the top earners in the US have grown, the likelihood that someone remains in the Top 1% from one year to the next, hasn't changed.

.. analyzing income mobility is valuable although it requires access to panel data. Saez and Veall (2005) and Kopcuzk, Saez, and Song (2010) have analyzed jointly inequality and mobility for at the top of the individual wage earnings distributions in Canada and the United States. They found that mobility, measured as the probability to drop out of the top percentile from one year to the next, has been remarkably stable over the last decades even though top wage earnings shares surged in both countries. As a result, increased mobility did not mitigate increases in annual top earnings shares.

While Income studies rely on tax data, Wealth4 inequality research are usually based on surveys. For wealth studies in the US a popular data source is the Survey of Consumer Finances administered by the Federal Reserve Board, a "triennial survey of the balance sheet, pension, income, and other demographic characteristics of U.S. families." In the graph below I use two notions of wealth as defined in Wolff (2010) (pp. 7-8)5:

Net Worth: "The principal wealth concept used here is marketable wealth (or net worth), which is defined as the current value of all marketable or fungible assets less the current value of debts. Net worth is thus the difference in value between total assets and total liabilities or debt. Total assets are defined as the sum of: (1) the gross value of owner-occupied housing; (2) other real estate owned by the household; (3) cash and demand deposits; (4) time and savings deposits, certificates of deposit, and money market accounts; (5) government bonds, corporate bonds, foreign bonds, and other financial securities; (6) the cash surrender value of life insurance plans; (7) the cash surrender value of pension plans, including IRAs, Keogh, and 401(k) plans; (8) corporate stock and mutual funds; (9) net equity in unincorporated businesses; and (10) equity in trust funds. Total liabilities are the sum of: (1) mortgage debt; (2) consumer debt, including auto loans; and (3) other debt."

Non-home Wealth: "This is defined as net worth minus net equity in owner-occupied housing (the primary residence only). Non-home wealth is a more liquid concept than marketable wealth, since one's home is difficult to convert into cash in the short term. Moreover, primary homes also serve a consumption purpose besides acting as a store of value. Non-home wealth thus reflects the resources that may be immediately available for consumption expenditure or various forms of investments."

The oft-quoted statistic - the Top 1% own 40% - can be seen from the graph below:

Net Worth: In 2007 the Top 1% households accounted for 34.6% , compared to 14.9% for the Bottom 80%.

Non-home Wealth: In 2007 the Top 1% households accounted for 42.7% , compared to 7% for the Bottom 80%.

Just as Income Inequality in the US has increased since the early 1980's, the share of total net worth owned by the Top 5% has also risen (from 56% in 1982 to 62% in 2007) - albeit at a slower rate. From 1983 to 2007 the share of total net worth owned by the Bottom 80% dropped from 18.7% to 14.9%

(2) Around 1949: "1939 for Indonesia, 1943 for Ireland, 1950 for Germany and the Netherlands, 1954 for Spain." ; Around 2005: "1995 for Switzerland, 1998 for Germany, 1999 for Netherlands, 1999-2000 for India, 2000 for Canada and Ireland, 2002 for Australia, 2003 for Portugal, 2004 for Argentina, Italy, Norway and Sweden."